Haihe River Basin Research Articles

A Sustainability Index for Evaluating Vegetation Restoration Under Rainwater Resources Limitation

AbstractEvaluating vegetation restoration sustainability is crucial to avoid conflicts between human water demand and ecosystem consumption, especially with the surge in leaf area index (LAI) due to revegetation projects in China. However, current methods for assessing vegetation sustainability are still limited. Here, we developed a sustainability index for vegetation systems (vegetation sustainability index, VSI) from water demand and supply aspects based on reliability, resilience, and vulnerability in arid and semi‐arid areas. VSI was built upon a vegetation overplanting index (dLAI) which is the difference between the maximum LAI supported by precipitation (LAIp) and the observed LAI (LAIobs). A case study in the mountainous area of the Haihe River basin reveals gradually declining VSI after 2000. Forests are the primary vegetation type in areas with VSI < 0.5, indicating decreased sustainability due to overplanting. The framework of VSI can be a useful tool for planning and implementing vegetation restoration strategies in arid and semi‐arid regions.

Potential impacts of land use and land cover change (LUCC) and climate change on evapotranspiration and gross primary productivity in the Haihe River Basin, China

Both land use and land cover change (LUCC) and global warming play crucial roles in regulating water and carbon exchanges between the surface and atmosphere. However, the individual contributions of LUCC and global warming, particularly in the mid-latitudes, remain poorly understood. This study disentangled the impacts of LUCC and global warming on evapotranspiration (ET) and gross primary productivity (GPP) during 1980–2015 in the Haihe River Basin (HRB), China, using the Community Land Model version 5. The model experiments suggest that decreases in natural vegetation and expansions of croplands in the HRB reduced annual GPP and ET. Conversely, increasing natural vegetation coverage enhanced annual GPP and ET. Neither LUCC nor global warming exhibited a statistically significant (p < 0.05) impact on the spatially averaged annual ET during 1980–2015. However, both LUCC and global warming significantly (p < 0.05) increased spatially averaged annual GPP. LUCC enhanced the spatially averaged GPP, possibly due to reforestation and afforestation since the late 1990s. Global warming increased GPP mainly due to the CO2 fertilization effect. When averaging across the whole HRB, LUCC increased ET with a magnitude of approximately 3.5 mm yr−1 between 1980 and 2015, while global warming reduced ET by about 3.0 mm yr−1. On average, LUCC enhanced the spatially averaged annual GPP with a comparable magnitude to global warming. The findings demonstrated that natural vegetation restoration emerges as an important strategy for climate warming mitigation in mid-latitudes experiencing intense anthropogenic disturbances.

Multi-evidences investigation into spatiotemporal variety, sources tracing, and health risk assessment of surface water nitrogen contamination in China

A comprehensive understanding of nitrogen pollution status, especially the identification of sources and fate of nitrate is essential for effective water quality management at the local scale. However, the nitrogen contamination of surface water across China was poorly understood at the national scale. A dataset related to nitrogen was established based on 111 pieces of literature from 2000 to 2020 in this study. The spatiotemporal variability, source tracing, health risk assessment, and drivers of China's surface water nitrogen pollution were analyzed by integrating multiple methods. These results revealed a significant spatiotemporal heterogeneity in the nitrogen concentration of surface water across China. Spatially, the Haihe River Basin and Yellow River Basin were the basins where surface water was seriously contaminated by nitrogen in China, while the surface water of Southwest Basin was less affected. Temporally, significant differences were observed in the nitrogen content of surface water in the Songhua and Liaohe River Basin, Pearl River Basin, Southeast Basin, and Yellow River Basin. There were 1%, 1%, 12%, and 46% probability exceeding the unacceptable risk level (HI＞1) for children in the Songhua and Liaohe River Basin, Pearl River Basin, Haihe River Basin, and Yellow River Basin, respectively. The primary sources of surface water nitrate in China were found to be domestic sewage and manure (37.7%), soil nitrogen (31.7%), and chemical fertilizer (26.9%), with a limited contribution from atmospheric precipitation (3.7%). Human activities determined the current spatiotemporal distribution of nitrogen contamination in China as well as the future development trend. This research could provide scientifically reasonable recommendations for the containment of surface water nitrogen contamination in China and even globally.

Impact of Urbanization-Driven Land Use Changes on Runoff in the Upstream Mountainous Basin of Baiyangdian, China: A Multi-Scenario Simulation Study

Urbanization in the Haihe River Basin in northern China, particularly the upstream mountainous basin of Baiyangdian, has significantly altered land use and runoff processes. The runoff is a key water source for downstream areas like Baiyangdian and the Xiong’an New Area, making it essential to understand these changes’ implications for water security. However, the exact implications of these processes remain unclear. To address this gap, a simulation framework combining SWAT+ and CLUE-S was used to analyze runoff responses under different land use scenarios: natural development (ND), farmland protection (FP), and ecological protection (EP). The model simulation results were good, with NSE above 0.7 for SWAT+. The Kappa coefficient for CLUE-S model validation was 0.83. The further study found that from 2005 to 2015, urban construction land increased by 11.50 km2 per year, leading to a 0.5–1.3 mm rise in annual runoff. Although urban expansion continued, the other scenarios, which emphasized farmland and forest preservation, slowed this growth. Monthly runoff changes were most significant during the rainy season, with annual runoff in ND, FP, and EP varying by 8.9%, 10.9%, and 7.7%, respectively. While the differences in annual runoff between scenarios were not dramatic, these findings provide a theoretical foundation for future water resource planning and management in the upstream mountainous area of Baiyangdian and offer valuable insights for the sustainable development of Xiong’an New Area. Additionally, these results contribute to the broader field of hydrology by highlighting the importance of considering multiple land use scenarios in runoff change analysis.

Landslides triggered by the July 2023 extreme rainstorm in the Haihe River Basin, China

Landslides triggered by the July 2023 extreme rainstorm in the Haihe River Basin, China

The response of agricultural drought to meteorological drought modulated by air temperature

Due to climate change, there is an increasing occurrence of combined extreme events. The interaction between agricultural drought and meteorological drought may be significantly influenced by the temperature conditions. However, the specific process and the extent of air temperature’s impact on the dynamic remain unknown. To this end, the present study develops a copula-based coupling model to integrate agricultural drought, meteorological drought, and temperature state. This model is designed to investigate how temperature affects the agricultural drought response to meteorological drought, and to determine the transition threshold of temperature state on agricultural drought responding to meteorological drought from inhibition to promotion under diverse drought conditions. Furthermore, the proposed model is used to explore the spatial distribution characteristics of sensitivity and temperature thresholds in summer over mainland China. Finally, the geographical detector model is employed to investigate the primary factors influencing the spatial distribution of sensitivity and temperature thresholds. Results indicated that: (1) high temperatures have intensified the response of agricultural drought to meteorological drought in over 88% of mainland China, while in the Qinghai-Tibet Plateau region of the Inland River basin, this response is mitigated by glacier meltwater resulting from high temperatures; (2) the thresholds are lower in the Southeast River basin, the lower reaches of the Yangtze River, the Pearl River basin, the southern Songliao River basin and the Haihe River basin, but higher in the Yellow River basin, the western Yangtze River basin, the southern Inland River basin and Yunnan Province; and (3) the land-atmosphere coupling is crucial in determining both sensitivity and threshold levels.

Effects of vegetation restoration on runoff and its components in the mountainous Haihe River Basin

Study regionTwo typical mountainous Haihe River Basins: The Xiaojue Basin and the Yehe River Basin Study focusesThe mountainous Haihe River Basin has suffered from a water crisis duo to large-scale restoration. Quantifying the hydrological impacts of vegetation restoration is necessary for local water management. In this study, we used the Soil and Water Assessment Tool (SWAT) hydrological model, in combination with two vegetation restoration scenarios, to analyze the effects of vegetation restoration on runoff and its runoff components (surface runoff, baseflow, and total runoff) New hydrological insights for the regionOur results indicated a general decrease in surface runoff and an increase in baseflow as a result of vegetation restoration. At the seasonal timescale, total runoff and surface runoff decreases mainly concentrated in the flood season, and slightly increased in the non-flood season, and baseflow showed the opposite trend during the flood-season in the Xiaojue and Yehe River Basin. The magnitude of change in runoff components in the Yehe River Basin was higher than that in the Xiaojue Basin, and the Yehe River Basin has a larger water yield capability. This study advances our knowledge on the way in which vegetation affects runoff and offers recommendations for water resources management

Enhancing short-term streamflow prediction in the Haihe River Basin through integrated machine learning with Lasso.

With the widespread application of machine learning in various fields, enhancing its accuracy in hydrological forecasting has become a focal point of interest for hydrologists. This study, set against the backdrop of the Haihe River Basin, focuses on daily-scale streamflow and explores the application of the Lasso feature selection method alongside three machine learning models (long short-term memory, LSTM; transformer for time series, TTS; random forest, RF) in short-term streamflow prediction. Through comparative experiments, we found that the Lasso method significantly enhances the model's performance, with a respective increase in the generalization capabilities of the three models by 21, 12, and 14%. Among the selected features, lagged streamflow and precipitation play dominant roles, with streamflow closest to the prediction date consistently being the most crucial feature. In comparison to the TTS and RF models, the LSTM model demonstrates superior performance and generalization capabilities in streamflow prediction for 1-7 days, making it more suitable for practical applications in hydrological forecasting in the Haihe River Basin and similar regions. Overall, this study deepens our understanding of feature selection and machine learning models in hydrology, providing valuable insights for hydrological simulations under the influence of complex human activities.

Preliminary analysis on the characteristics of light absorption coefficients in typical rivers of different river basins across China

As a vital constituent of water’s optical properties, the absorption coefficients influence the distribution of underwater light field, consequently impacting the structures and functional patterns of riverine ecosystems. In this study, the light absorption of non-algal particulates (ad(λ), m−1), phytoplankton (aph(λ), m−1) and CDOM (ag(λ), m−1) of 380 water samples collected from 133 rivers in eight external river basins across China from 2013 to 2023 were examined to determine the optical absorption characteristics. Results showed significant differences in ad(λ), aph(λ) and ag(λ) across different basins. ① The water bodies of eight basins can be categorized into 5 dominant types of absorption coefficients. ② In eastern China, ag(440) exhibited a northeast-high and southwest-low spatial distribution pattern. The Songliao River Basin had the highest ag(440) than other basins. The higher slope S of ag(λ) in rivers compared to lakes and reservoirs confirm river water primarily derive CDOM from external sources, distinguishing them from lakes and reservoirs. ③ The Huaihe and Haihe River Basins had higher ad(440) and aph(440) values, primarily due to lower terrain and human activities, leading to the accumulation of suspended particles and nutrients. And soil erosion from the Loess Plateau caused significant differences in ad(440) between the upper and middle reaches of the Yellow River Basin. These findings hold significant implications for understanding the optical characteristics of rivers in China.

Effects of drought on ecosystem evapotranspiration and gross primary productivity in the Haihe River Basin

Evapotranspiration is a crucial component of the hydrological cycle and Gross Primary Productivity (GPP) is the largest flux in the global carbon cycle. However, both evapotranspiration and GPP are significantly affected by climate disasters, especially extreme drought events. Therefore, in this study, MODIS product data from 2002 to 2021 was used to analyze the spatiotemporal variations of actual evapotranspiration (ET), potential evapotranspiration (PET) and GPP within the Haihe River Basin. Then extreme drought events were identified by using EDDI drought index. A statistical analysis was performed to assess the impact of extreme drought on ecosystem evapotranspiration and GPP. The results showed that: (1) the annual evapotranspiration in the Haihe River Basin fluctuated greatly, ET showed a general increasing trend which was higher in the eastern region and lower in the central and western regions, PET showed an overall decreasing trend which was higher in the central and western regions and lower in the eastern region; (2) the annual GPP in the Haihe River Basin from 2002 to 2021 was 646.88 g C/m2/a and the increase rate was 14.75 g C/m2/a, which exhibited a decreasing trend from the northern to the southern and central-western regions; (3) under extreme drought conditions, ET decreased compared with the mean value, while PET increased, the Zhangweihe and the Tuhaimajiahe sub-basins were the most affected, with ET decreasing by 16.36% and PET increasing by 7.00% compared to the reference year. Additionally, extreme drought led to a decrease in GPP, with a reduction ranging from 7% to 18%.

Spatial-temporal change of river thermal environment and anthropogenic impact in China

River water temperature is important and closely related to river ecosystem, concerning fishery industry, human health, and the land-sea exchange of nutrients, especially for great powers with a good deal of heat emission from once-through cooling systems of thermal power plants. However, the changes in river water temperature under the joint action of climate change and human activity such as the heat emission have not been well investigated for rising powers, hampering environmental policy making for sustainable development. Therefore, we have taken advantage of a recently-developed land surface model including river water temperature calculation with anthropogenic thermal discharge and zonal statistics to quantitatively make out the river water temperature variation and the man-made influence over the past thirty years (1981–2010) in China for the first time. Results show that the estimated water temperature in major rivers is generally close to the observation with the r2 of 0.83, though the underestimation exists in some rivers. The river water in the Pearl River Basin was the warmest with the mean temperature of 19.2 °C and the others in order were in the Southeast Basin, the Huaihe River Basin, the Yangtze River Basin, the Haihe River Basin, the Yellow River Basin, the Southwest Basin, the Song-Liao River Basin, and the Continental Basin, ranging from 16.7 °C to 6.3 °C. The Huaihe River Basin had the fastest mean increase rate of ca. 0.27 °C decade−1, while the slowest mean increase rate of ca. 0.13 °C decade−1 existed in the Pearl River Basin. At the subbasin scale, a meridionally-distributed hot spot zone (along the 115°E) of the increasing water temperature has been identified, where the trends ranged from 0.2 °C decade−1 to 0.5 °C decade−1. Air temperature exerted a major control on the spatial pattern of climatological water temperature, while both air temperature and downwelling solar flux played a leading role in the distribution of water temperature change trends. Although anthropogenic thermal emission heated the rivers locally, the impacts in the Song-Liao River, the Haihe River, the Huaihe River, and the middle and lower reaches of Yellow River and Yangtze River had been raised up to ca. 4.5 °C, when comparing with those controlled by climate change only. In general, these results show an acceptable level of river water temperature simulation in the land surface model, and could provide a scientific reference for the assessment on riverine thermal environment under the climate change and social impact in China.

A complex network perspective on spatiotemporal propagations of extreme precipitation events in China

Extreme precipitation events (EPEs) cause catastrophic losses to human lives and social economy. Focusing on the wet season from May to October, this paper formulates the complex network to characterize the spatiotemporal propagations of EPEs over 218 river basins in China. Specifically, based on the daily Multi-Source Weighted-Ensemble Precipitation version 2, the event synchronization along with significance test facilitates the complex network of EPEs from 1979 to 2020. By characterizing the topology of EPEs, the results show that synchronous EPEs generally occur over the Hetao Area of Yellow River Basin, Haihe River Basin and Northeast China. The complex network of EPEs classifies the 218 river basins into six communities. In May and June, more than 50 % of EPEs generally occur in South China. From July to September, over 60 % of EPEs tend to be observed in the Huang-Huai-Hai Plain, upper-middle reaches of Yellow River Basin, Northeast China and Southwest China. In October, about 65 % of EPEs happen in South and Southwest China. In the meantime, less than 10 % of EPEs occur in Northwest China. Among the synchronous EPEs starting in late June or early July and peaking in late July to early August, there exist propagations along the Yellow River, Haihe, Liaohe and Songhua River Basin within one to eight days. Eastward moisture transport along this pathway within four to six days drives the propagation of synchronous EPEs. The complex network analysis of this paper provides useful information for early warning and forecasting of EPEs and flood hazards.

2013–2020年海河流域农田水热碳通量及气象要素观测数据集

The present study area was located in the cropland ecosystem near Guanting Reservoir in Haihe River Basin. We conducted long-term observations of the multi-scale fluxes and meteorological elements, using various observation systems, including lysimeter, eddy covariance, large aperture scintillometer and automatic weather station/gradient of meteorological elements. This dataset consists of multi-scale fluxes (meter, hundred-meter, and kilometer-meter) and meteorological elements data. Observation items include ecosystem net carbon exchange, latent heat flux/evapotranspiration, sensible heat flux, air temperature, relative humidity, wind speed, wind direction, downward/upward shortwave radiation, downward/upward longwave radiation, net radiation, atmospheric pressure, precipitation, infrared radiation temperature, photosynthetic effective radiation, soil temperature, soil moisture, soil heat flux, and average soil temperature, etc. This dataset is processed carefully and can be used to study the effects of reservoir expansion and shrinkage on the circulation of carbon and water or other substances in the surrounding ecosystem. Additionally, it can serve as a powerful data basis for the research on relevant remote sensing estimation and model simulation.

Spatiotemporal distribution of ecological risk of antibiotics in seven major river basins of China: An optimized multilevel assessment approach.

Antibiotics have been recognized as emerging pollutants due to their ecological and human health risks. This paper aims to enhance the ecological risk assessment (ERA) framework for antibiotics, to illustrate the distribution of these risks across different locations and seasons, and to identify the antibiotics that pose high ecological risk. This paper focuses on 52 antibiotics in seven major basins of China. Relying on the optimized approach of ERA and antibiotic monitoring data published from 2017 to 2021, the results of ERA are presented in multilevel. Across the study area, there are marked variations in the spatial distribution of antibiotics' ecological risks. The Huaihe River Basin, the Haihe River Basin, and the Liaohe River Basin are the top three in the ranking of present ecological risks. The research results also reveal significant differences in temporal variation, underscoring the need for increased attention during certain seasons. Ten antibiotics with high contribution rates to ecological risk are identified, which is an important reference to formulate an antibiotic control list. The multilevel results provided both risk values and their ubiquities across a broad study region, which is a powerful support for developing ecological risk management of antibiotics.

A chromosome-level genome assembly of East Asia endemic minnow Zacco platypus

Zacco platypus is an endemic colorful freshwater minnow that is intensively distributed in East Asia. In this study, two adult female individuals collected from Haihe River basin were used for karyotypic study and genome sequencing, respectively. The karyotype formula of Z. platypus is 2N = 48 = 18 M + 24SM/ST + 6 T. We used PacBio long-read sequencing and Hi-C technology to assemble a chromosome-level genome of Z. platypus. As a result, an 814.87 Mb genome was assembled with the PacBio long reads. Subsequently, 98.64% assembled sequences were anchored into 24 chromosomes based on the Hi-C data. The chromosome-level assembly contained 54 scaffolds with a N50 length of 32.32 Mb. Repeat elements accounted for 52.35% in genome, and 24,779 protein-coding genes were predicted, with 92.11% were functionally annotated with the public databases. BUSCO analysis yielded a completeness score of 96.5%. This high-quality genome assembly provides valuable resources for future functional genomic research, comparative genomics, and evolutionary studies of genus Zacco.

Comprehensive Assessment of Environmental Emissions, Fate, and Risks of Veterinary Antibiotics in China: An Environmental Fate Modeling Approach.

China is one of the major global consumers of veterinary antibiotics. Insufficient recognition of emissions and environmental contamination hamper global efforts to prevent antibiotic resistance development. This pioneering study combined empirical data and modeling approaches to predict total 2010-2020 emissions of 80 veterinary antibiotics ranging from 23,110 to 40,850 tonnes/year, after 36-50% antibiotic removal by manure treatment. Following an initial increase of 10% from 2010 to 2015, emissions declined thereafter by 43%. While 85% of emissions discharged into soils, approximately 56%, 23%, and 18% of environmental residue were ultimately distributed in soils, freshwaters, and seawaters under steady-state conditions. In 2020, 657 (319-1470) tonnes entered the ocean from inland freshwaters. Median ∑antibiotics concentrations were estimated at 4.7 × 103 ng/L in freshwaters and 2.9 ng/g in soils, with tetracyclines and sulfonamides as the predominant components. We identified 44 veterinary antibiotics potentially posing high risks of resistance development in freshwaters, with seven exhibiting high risks in >10% of Chinese freshwater areas. Tetracyclines were the category with the most antibiotics exhibiting elevated risks; however, sulfamethylthiazole demonstrated the highest individual compound risk. The Haihe River Basin displayed the highest susceptibility overall. The findings offer valuable support for control of veterinary antibiotic contamination in China.

Analysis and Simulation of Land Use Changes and Their Impact on Carbon Stocks in the Haihe River Basin by Combining LSTM with the InVEST Model

The quantitative analysis and prediction of spatiotemporal patterns of land use in Haihe River Basin are of great significance for land use and ecological planning management. To reveal the changes in land use and carbon stock, the spatial–temporal pattern of land use data in the Haihe River Basin from 2000 to 2020 was studied via Mann–Kendall (MK) trend analysis, the transfer matrix, and land use dynamic attitude. Through integrating the models of the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and the Long Short-Term Memory (LSTM), the results of the spatial distribution of land use and carbon stock were obtained and compared with Cellular Automation (CA-Markov), and then applied to predict the spatial distribution in 2025. The results show the following: (1) The land use and land cover (LULC) changes in the Haihe River Basin primarily involve an exchange between cultivated land, forest, and grassland, as well as the conversion of cultivated land to built-up land. This transformation contributes to the overall decrease in carbon storage in the basin, which declined by approximately 1.20% from 2000 to 2020. (2) The LULC prediction accuracy of LSTM is nearly 2.00% higher than that of CA-Markov, reaching 95.01%. (3) In 2025, the area of grassland in Haihe River Basin will increase the most, while the area of cultivated land will decrease the most. The spatial distribution of carbon stocks is higher in the northwest and lower in the southeast, and the changing areas are scattered throughout the study area. However, due to the substantial growth of grassland and forest, the carbon stocks in the Haihe River Basin in 2025 will increase by about 10 times compared with 2020. The research results can provide a theoretical basis and reference for watershed land use planning, ecological restoration, and management.

Effects of Land Use Types on Water Quality at Different Buffer Scales: Tianjin Section of the Haihe River Basin as an Example

It is important to explore the relationship between land use types and water quality to improve the surface water environment. Based on monthly water quality monitoring data from 16 nationally controlled surface water quality monitoring stations in Tianjin and land use data in 2021, GIS spatial analysis and mathematical and statistical methods were used to study the influence of land use types on surface water quality in buffer zones at different scales. The results showed that:① the land use types in the study area were mainly construction land, farmland, and water areas, which had significant effects on river water quality. Except for water temperature (WT) and pH, the farmland, construction land, and water areas were negatively correlated with each water quality indicator; forest land and grassland were positively correlated with dissolved oxygen (DO) and total nitrogen (TN) and negatively correlated with other water quality indicators. ② The water quality indicators showed obvious spatial differences in different seasons. The pH, DO and TN concentrations were higher in the dry season, whereas the permanganate index, ammonia nitrogen (NH4+-N), and total phosphorus (TP) concentrations were higher in the rainy season. ③ The results of the RDA analysis showed that the 800 m buffer zone land use had the greatest explanatory power for water quality changes in the dry season (50.4%), whereas the 3 000 m buffer zone land use could explain the water quality changes in the rainy season to the greatest extent (49.6%); from the average explanation rate of the dry and rainy seasons, the 3 000 m buffer zone was the best impact scale (50.0%) on water quality indicators in Tianjin. ④ The partial least squares regression (PLSR) analysis showed that the most important variables affecting surface water quality changes were construction land, farmland, and water areas. The predictive ability of the PLSR model of most water quality indicators was stronger in the dry season than that in the rainy season. In the dry season, all water quality indicators, except WT and pH, were most influenced by farmland. In the rainy season, construction land had the greatest influence on WT and NH4+-N concentrations, and the most important influencing factor for the remaining water quality indicators was still farmland. This study showed that the rational planning of land use types within 3 000 m of rivers or lakes was beneficial to improving the water quality of surface water.

Spatial Heterogeneity and the Increasing Trend of Vegetation and Their Driving Mechanisms in the Mountainous Area of Haihe River Basin

In addition to serving as North China’s water supply and ecological barrier, the mountainous area of the Haihe River basin (MHRB) is a crucial location for the application of ecological engineering. Vegetation is an important component in the ecological conservation and eco-hydrological progress of the MHRB. A better understanding of regional vegetation growth can be achieved by a thorough investigation of vegetation indicators. In this research, the leaf area index (LAI) and gross primary productivity (GPP) were chosen as vegetation indicators. The characteristics and driving forces of the spatiotemporal variations of LAI and GPP in the MHRB were explored through Sen’s slope, the Mann–Kendall test, the optimal parameter-based geographical detector model, and correlation analysis. From 2001 to 2018, the annual LAI and GPP increased significantly on the regional scale. The areas with significantly increased vegetation accounted for more than 81% of the MHRB. Land use was the most influential element for the spatial heterogeneity of LAI and GPP, and the humidity index was the most crucial one among climate indicators. Non-linear enhancement or bivariate enhancement was discovered between any two factors, and the strongest interaction was from land use and humidity index. The lowest vegetation cover was found in dry regions with annual precipitation below 407 mm and the humidity index under 0.41; while in both forests and large undulating mountains, higher LAI and GPP were observed. About 87% of the significantly increased vegetation was found in areas with unaltered land use. The increase in vegetation in the MHRB from 2001 to 2018 was promoted by the increased precipitation and humidity index and the reduced vapor pressure deficit. The sensitivity of GPP to climate change was stronger than that of LAI. These findings can serve as a theoretical guide for the application of ecological engineering and ecological preservation in the MHRB.

Response of Typical Tree Species Sap Flow to Environmental Factors in the Hilly Areas of Haihe River Basin, China

Understanding developments in the trunk sap flow of prevalent tree species within the hilly areas of the Haihe River basin is imperative for ecosystem conservation. Nevertheless, the changes in sap flow of local trees and their response to environmental factors remain elusive. This study focuses on seven dominant tree species in the hilly area of the Haihe River basin and analyzed the relationship between tree sap flow rate and environmental factors at different time scales (hourly and daily). Our findings suggested: (1) Regardless of the time scale, total solar irradiance played a primary role in influencing sap flow rate. Conversely, as the time scale grew, the associations between most soil factors and sap flow rate enhanced, while those with meteorological factors declined. Notably, soil temperature exerted a more profound influence on sap flow rate than soil moisture and conductivity. (2) At the hourly scale, the sap flow rate of each species had a lag effect of 1–2 h with vapour pressure deficit, relative humidity and temperature, and 1 h or no lag effect with total solar irradiance and wind speed. (3) The response model of sap flow rate and environmental factors showed that, except for Pinus tabuliformis Carr., other tree species fit well at various time scales (R2 ≥ 0.59). As the time scale of most tree species increased from hourly scale to daily scale, the fit gradually weakened. Concurrently, considering the time-lag effect, the accuracy of the model has been improved, and the fitting accuracy of Koelreuteria paniculata Laxm. and Pinus tabuliformis Carr. has been significantly improved.